vivoBodySeg: Machine learning-based analysis of C. elegans immobilized in vivoChip for automated developmental toxicity testing.

Developmental toxicity (DevTox) tests evaluate the adverse effects of chemical exposures on an organism's development. While large animal tests are currently heavily relied on, the development of new approach methodologies (NAMs) is encouraging industries and regulatory agencies to evaluate these novel assays. Several practical advantages have made C. elegans a useful model for rapid toxicity testing and studying developmental biology. Although the potential to study DevTox is promising, current low-resolution and labor-intensive methodologies prohibit the use of C. elegans for sub-lethal DevTox studies at high throughputs. With the recent availability of a large-scale microfluidic device, vivoChip, we can now rapidly collect 3D high-resolution images of ~ 1,000 C. elegans from 24 different populations. In this paper, we demonstrate DevTox studies using a 2.5D U-Net architecture (vivoBodySeg) that can precisely segment C. elegans in images obtained from vivoChip devices, achieving an average Dice score of 97.80. The fully automated platform can analyze 36 GB data from each device to phenotype multiple body parameters within 35 min on a desktop PC at speeds ~ 140× faster than the manual analysis. Highly reproducible DevTox parameters (4-8% CV) and additional autofluorescence-based phenotypes allow us to assess the toxicity of chemicals with high statistical power.

The impact of basal cell carcinoma on the quality-of-life in older patients.

Basal cell carcinoma (BCC) is the most frequent malignant tumour worldwide and incidences are rising rapidly. BCC grow locally, but can invade surrounding tissues. Little is known concerning their impact on the health-related quality of life (HrQoL), and limited available data reports contradicting results. Measuring HrQoL in BCC patients should be done using disease-specific questionnaires such as the Basal and Squamous cell carcinoma Quality of Life (BaSQoL) questionnaire. The aim of this study was to assess the BCC-related HrQoL by examining all relevant patient, tumour and treatment characteristics to identify the main factors for the BCC-related impact. Specific attention for older BCC patients wass brought forward because of the often complex decisions in this subgroup. Patients ≥ 18 years with a history of BCC were asked to fill in the BaSQoL questionnaire, consisting of 5 subdomains. Multivariable analyses were done using a generalized additive model (GAM) because of the need for incorporation of non-linear functions. The study obtained approval of the Ethics Committee of the Ghent University Hospital (EC/2019/1352). Informed consent was obtained from all subjects. All experiments were performed in accordance with relevant guidelines and regulations. Four hundred patients with a median age of 66 were enrolled. Mean BaSQoL subscores were 0.78 (SD 0.63) for 'behaviour', 1.01 (SD 0.73) for 'diagnosis&treatment', 0.90 (SD 0.73) for 'worries', 0.40 (SD 0.63) for 'appearance' and 1.20 (SD 0.75) for 'other people', illustrating the low to moderate impact of BCC on the HrQoL. A GAM with subsequent ANOVA testing was done for all relevant variables. In 4 out of 5 BaSQoL subdomains 'age' showed a significant correlation ('behaviour' p = 0.007; 'diagnosis&treatment' p = 0.026; 'worries' p = 0.003; 'appearance' p = 0.008). Lower BaSQoL scores were seen in older patients, meaning less BCC-impact on their HrQoL. There was a clear non-linear correlation between BaSQoL scores and age, illustrating that the impact of BCC on the HrQoL shows a rapid decrease starting around the age of 70. This study is the first to illustrate the relation between the BCC-related HrQoL and the age of patients with the use of a disease-specific HrQoL instrument. We found a lower BaSQoL score in older adults, with a specific age group of interest starting around the age of 70-75. This is an argument for a potential wait-and-see strategy for BCC in these patients.

Leveraging single-cell ATAC-seq and RNA-seq to identify disease-critical fetal and adult brain cell types.

Prioritizing disease-critical cell types by integrating genome-wide association studies (GWAS) with functional data is a fundamental goal. Single-cell chromatin accessibility (scATAC-seq) and gene expression (scRNA-seq) have characterized cell types at high resolution, and studies integrating GWAS with scRNA-seq have shown promise, but studies integrating GWAS with scATAC-seq have been limited. Here, we identify disease-critical fetal and adult brain cell types by integrating GWAS summary statistics from 28 brain-related diseases/traits (average N = 298 K) with 3.2 million scATAC-seq and scRNA-seq profiles from 83 cell types. We identified disease-critical fetal (respectively adult) brain cell types for 22 (respectively 23) of 28 traits using scATAC-seq, and for 8 (respectively 17) of 28 traits using scRNA-seq. Significant scATAC-seq enrichments included fetal photoreceptor cells for major depressive disorder, fetal ganglion cells for BMI, fetal astrocytes for ADHD, and adult VGLUT2 excitatory neurons for schizophrenia. Our findings improve our understanding of brain-related diseases/traits and inform future analyses.

A spatial cell atlas of neuroblastoma reveals developmental, epigenetic and spatial axis of tumor heterogeneity.

Neuroblastoma is a pediatric cancer arising from the developing sympathoadrenal lineage with complex inter- and intra-tumoral heterogeneity. To chart this complexity, we generated a comprehensive cell atlas of 55 neuroblastoma patient tumors, collected from two pediatric cancer institutions, spanning a range of clinical, genetic, and histologic features. Our atlas combines single-cell/nucleus RNA-seq (sc/scRNA-seq), bulk RNA-seq, whole exome sequencing, DNA methylation profiling, spatial transcriptomics, and two spatial proteomic methods. Sc/snRNA-seq revealed three malignant cell states with features of sympathoadrenal lineage development. All of the neuroblastomas had malignant cells that resembled sympathoblasts and the more differentiated adrenergic cells. A subset of tumors had malignant cells in a mesenchymal cell state with molecular features of Schwann cell precursors. DNA methylation profiles defined four groupings of patients, which differ in the degree of malignant cell heterogeneity and clinical outcomes. Using spatial proteomics, we found that neuroblastomas are spatially compartmentalized, with malignant tumor cells sequestered away from immune cells. Finally, we identify spatially restricted signaling patterns in immune cells from spatial transcriptomics. To facilitate the visualization and analysis of our atlas as a resource for further research in neuroblastoma, single cell, and spatial-omics, all data are shared through the Human Tumor Atlas Network Data Commons at www.humantumoratlas.org.

Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution.

The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation and cancer. While coding variation in HLA genes has been extensively documented, regulatory genetic variation modulating HLA expression levels has not been comprehensively investigated. Here we mapped expression quantitative trait loci (eQTLs) for classical HLA genes across 1,073 individuals and 1,131,414 single cells from three tissues. To mitigate technical confounding, we developed scHLApers, a pipeline to accurately quantify single-cell HLA expression using personalized reference genomes. We identified cell-type-specific cis-eQTLs for every classical HLA gene. Modeling eQTLs at single-cell resolution revealed that many eQTL effects are dynamic across cell states even within a cell type. HLA-DQ genes exhibit particularly cell-state-dependent effects within myeloid, B and T cells. For example, a T cell HLA-DQA1 eQTL ( rs3104371 ) is strongest in cytotoxic cells. Dynamic HLA regulation may underlie important interindividual variability in immune responses.

Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution.

The human leukocyte antigen (HLA) locus plays a critical role in complex traits spanning autoimmune and infectious diseases, transplantation, and cancer. While coding variation in HLA genes has been extensively documented, regulatory genetic variation modulating HLA expression levels has not been comprehensively investigated. Here, we mapped expression quantitative trait loci (eQTLs) for classical HLA genes across 1,073 individuals and 1,131,414 single cells from three tissues, using personalized reference genomes to mitigate technical confounding. We identified cell-type-specific cis-eQTLs for every classical HLA gene. Modeling eQTLs at single-cell resolution revealed that many eQTL effects are dynamic across cell states even within a cell type. HLA-DQ genes exhibit particularly cell-state-dependent effects within myeloid, B, and T cells. Dynamic HLA regulation may underlie important interindividual variability in immune responses.

PBS3 and EPS1 Complete Salicylic Acid Biosynthesis from Isochorismate in Arabidopsis.

Salicylic acid (SA) is an important phytohormone mediating both local and systemic defense responses in plants. Despite over half a century of research, how plants biosynthesize SA remains unresolved. In Arabidopsis, a major part of SA is derived from isochorismate, a key intermediate produced by the isochorismate synthase, which is reminiscent of SA biosynthesis in bacteria. Whereas bacteria employ an isochorismate pyruvate lyase (IPL) that catalyzes the turnover of isochorismate to pyruvate and SA, plants do not contain an IPL ortholog and generate SA from isochorismate through an unknown mechanism. Combining genetic and biochemical approaches, we delineated the SA biosynthetic pathway downstream of isochorismate in Arabidopsis. We found that PBS3, a GH3 acyl adenylase-family enzyme important for SA accumulation, catalyzes ATP- and Mg2+-dependent conjugation of L-glutamate primarily to the 8-carboxyl of isochorismate and yields the key SA biosynthetic intermediate, isochorismoyl-glutamate A. Moreover, we discovered that EPS1, a BAHD acyltransferase-family protein with a previously implicated role in SA accumulation upon pathogen attack, harbors a noncanonical active site and an unprecedented isochorismoyl-glutamate A pyruvoyl-glutamate lyase activity that produces SA from the isochorismoyl-glutamate A substrate. Together, PBS3 and EPS1 form a two-step metabolic pathway to produce SA from isochorismate in Arabidopsis, which is distinct from how SA is biosynthesized in bacteria. This study closes a major knowledge gap in plant SA metabolism and would help develop new strategies for engineering disease resistance in crop plants.